Laser & Optoelectronics Progress, Volume. 57, Issue 4, 041018(2020)
CV Image Segmentation Model Combining Convolutional Restricted Boltzmann Machine
Traditional image segmentation methods mainly rely on the low-level features, such as image spectrum and texture, and are easily disturbed by occlusion and shadow. To address these problems, a CV (Chan-Vest) image segmentation model combining the convolutional restricted Boltzmann machine is proposed. The target shape a priori information is modeled and generated using the convolutional restricted Boltzmann machine. Then the energy function of the CV model is constrained by the added a priori shape term to guide image segmentation. Better segmentation results are obtained in remote sensing datasets Satellite-2000 and Vaihigen, whose training data are limited while target shapes and sizes are different.
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Xiaohui Li, Xili Wang. CV Image Segmentation Model Combining Convolutional Restricted Boltzmann Machine[J]. Laser & Optoelectronics Progress, 2020, 57(4): 041018
Category: Image Processing
Received: Jul. 29, 2019
Accepted: Sep. 27, 2019
Published Online: Feb. 20, 2020
The Author Email: Wang Xili (wangxili@snnu.edu.cn)